ActiveMem: Distributed Active Memory for Long-Horizon LLM Reasoning

• URL: http://arxiv.org/abs/2606.10532v1
• Date: Tue, 09 Jun 2026 08:03:38 GMT
• Title: ActiveMem: Distributed Active Memory for Long-Horizon LLM Reasoning
• Abstract summary: Memory is essential for enabling large language model (LLM) agents to handle long-horizon reasoning tasks.<n>We propose ActiveMem, a framework that decouples agent memory from the core reasoning process.<n>Experiments on BrowseComp-Plus and GAIA show that ActiveMem achieves state-of-the-art accuracy with significantly reduced overhead.
• Score: 46.225019133047965
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Memory is essential for enabling large language model (LLM) agents to handle long-horizon reasoning tasks. Existing memory mechanisms are largely centralized, typically organizing retrieved information and interaction history within a single model context. This design imposes a fundamental trade-off: scaling reasoning trajectories risks context overload, whereas aggressive content pruning may result in irreversible information loss. Seeking a better trade-off, we draw inspiration from human cognitive systems, especially the functional complementarity between the prefrontal cortex (executive control) and the hippocampus (memory management), suggesting that such a trade-off need not be inherent, but may instead stem from centralized memory organization. To this end, we propose ActiveMem, a heterogeneous framework that decouples agent memory from the core reasoning process. Specifically, a high-level Planner utilizes distilled semantic gists to execute reasoning, while a lightweight, distributed memory system operates in parallel to actively accumulate and consolidate these gists throughout the task. Experiments on BrowseComp-Plus and GAIA show that ActiveMem achieves state-of-the-art accuracy with significantly reduced overhead, demonstrating the effectiveness of distributed active memory for long-horizon reasoning.

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